At present, a new round of scientific and technological revolution and industrial transformation are accelerating. Artificial intelligence has become an important force in promoting economic structural change and productivity growth. It is also an important technical force in promoting green development. Relying on data analysis, intelligent perception, prediction optimization and dynamic decision-making, artificial intelligence can improve the efficiency of resource allocation in industrial production, energy dispatch, transportation, building operation and other fields, reduce the intensity of energy consumption per unit of output, and accelerate the green and low-carbon transformation of the energy system. However, the green empowerment of smart technology must be based on a sustained and stable supply of computing power, and the formation and operation of computing power are inseparable from the support of electricity.
As large model training, agent applications and data center construction continue to advance, promoting the deep integration of computing systems and energy and power, promoting the mutual support of smart economic development and energy green transformation, is becoming an important focus in cultivating green productivity and shaping new competitive advantages in the smart economy. The 2026 "Government Work Report" proposed to "implement new infrastructure projects such as ultra-large-scale intelligent computing clusters and computing and electricity collaboration." The “15th Five-Year Plan” outline also clearly states that “promoting the coordinated layout of green power and computing power”. Computing and computing collaboration has risen from technology pilot to top-level design, becoming a key support for creating a new form of smart economy.
The so-called computing and electricity collaboration refers to a new infrastructure project that deeply integrates computing infrastructure and power systems through digital technology, intelligent algorithms, and information networks to promote dynamic matching and optimal allocation of resources, and achieve a virtuous cycle of using electricity to strengthen computing and using computing to promote electricity. As a key support for building a new form of smart economy, computing power synergy emphasizes the two-way empowerment of computing power and electricity. By increasing the proportion of green energy usage, optimizing computing power load allocation and improving computing power supply efficiency, it promotes the coordination of computing power expansion with green energy structure and efficient resource allocation, laying a solid green, efficient and sustainable energy foundation for the development of smart economy.
Optimize the energy consumption structure and consolidate the green energy foundation for the development of smart economy. Increasing the proportion of green energy in computing power consumption is a basic requirement to promote the green development of the smart economy. By coordinating the layout of computing power and green energy, computing power collaboration enhances the spatial adaptation of energy supply and computing power demand, and promotes the collaborative evolution of computing power expansion and green energy structure. On the one hand, it guides tasks with low latency requirements such as model training and offline calculations to be rationally distributed in new energy-rich areas to achieve "computing on the go" and improve the level of local consumption of new energy. On the other hand, relying on mechanisms such as cross-regional power transmission and green power trading, clean power is transported to areas with concentrated computing power needs to achieve "power on the go" and increase the proportion of green power usage in data centers such as the Eastern Intelligent Computing Center.
Improve allocation efficiency and reduce energy costs and carbon intensity of smart economic development. Forming more effective computing power supply under a given energy input is an important manifestation of promoting the green development of the smart economy. Computing and power collaboration can implement classified scheduling based on the real-time, continuity, and adjustability of different computing tasks, and enhance the timing adaptation of computing loads and green power supply: when green power supply is abundant, adjustable computing tasks are added, and when new energy output decreases or the grid load is high, elastic loads are appropriately reduced or migrated, and dynamic matching of computing tasks and energy supply is achieved through cross-regional computing power scheduling. This can not only improve new energy consumption capabilities, but also guide computing companies to proactively respond to time-sharing energy prices and supply conditions, reduce energy consumption per unit of computing power and carbon emissions per unit of output, improve computing power facility utilization efficiency and energy factor allocation efficiency, thereby improving the energy productivity of the smart economy.
Amplify the enabling effect and support the green transformation of the economy and society with the supply of high-quality green computing power. Promoting artificial intelligence to enter a wider range of real economy scenarios at lower costs is an important direction for the green development of the smart economy. By increasing the proportion of green power usage, reducing energy costs and enhancing supply stability, computing power collaboration improves the availability and economy of green computing power, and lowers the application threshold for artificial intelligence technology in manufacturing, energy, transportation, construction and other fields. As high-quality green computing power accelerates its penetration into the real economy, artificial intelligence can be more widely used in scenarios such as production process optimization, new energy prediction, intelligent dispatch, traffic management, building energy conservation and energy storage control, promoting the green effect of intelligent technology to extend from computing power infrastructure to the industrial chain and production process. As a result, green energy lays a solid foundation for the development of smart economy, and smart technology in turn improves energy and resource utilization efficiency, forming a virtuous cycle of using electricity to strengthen computing and computing to promote electricity.
The role of computing and computing collaboration in optimizing energy consumption structure, improving allocation efficiency, and amplifying the enabling effect can only be transformed into real productivity if it is embedded in the corresponding planning, operation, technology, and institutional systems. To this end, we must actively build a computing and computing collaboration system that is compatible with the new form of smart economy.
Strengthen overall planning and optimize the spatial layout of computing power and green energy. Promote the effective connection of computing power, electricity and new energy development plans during the "15th Five-Year Plan" period, coordinate the construction of computing power facilities, transmission channels and green energy bases, and develop new energy models such as nearby power supply, aggregation trading and local consumption. According to the delay requirements and power consumption characteristics of different computing tasks, optimize the spatial layout of the intelligent computing center, promote the coordinated construction of the "Eastern Data and West Computing" hub node and the "Shagohuang" large-scale wind and solar base, and guide the reasonable aggregation of delay-insensitive computing tasks to the green power-rich areas in the west; in the east, the collaboration between computing power facilities and local green energy such as offshore wind power and distributed photovoltaics will be strengthened to form a spatial configuration pattern that combines "computing with power" and "power with calculation".
Deepen collaborative operation and release the potential of flexible adjustment of computing power load. Strengthen the connection between the national integrated computing network and the power dispatching system, and promote the collaborative optimization of computing tasks, power supply, and network resources. Implement flexible scheduling of computing tasks that can be time-shifted, migrated, and interruptible based on changes in new energy output and grid load; support data centers in configuring energy storage, microgrids, and intelligent energy management systems, and participate in demand response through virtual power plants and other methods to promote the gradual transformation of computing power from rigid electricity loads to flexible regulation resources of the power system.
Strengthen technical support and improve the efficiency of collaborative computing and computing operations. Carry out collaborative research around key technologies such as joint prediction of computing load and new energy power, intelligent dispatch, flexible regulation, and advanced energy storage, and improve data interfaces, technical standards, and testing and evaluation systems. Establish a monitoring and evaluation mechanism covering indicators such as green power consumption, carbon emission intensity, computing power efficiency and load adjustability, strengthen collaborative sensing and dynamic analysis of cross-regional and cross-platform computing power and power resources, provide support for optimal dispatch and scientific decision-making, and improve the level of refinement and intelligence of collaborative computing and power operations.
Improve systems and mechanisms to enhance the endogenous power of computing and computing collaboration. Improve the green certificate and green electricity trading mechanism, improve the connection mechanism between time-of-use electricity prices, demand response compensation, and cross-regional power trading and computing power dispatching, promote large-scale wind and solar bases and large-scale computing power centers to carry out green electricity direct connection and point-to-point trading pilots, and guide the effective transmission of green power supply conditions and price signals to the computing power allocation link. Strengthen the connection between green power traceability, green certificate application and carbon emission accounting, explore cross-regional benefit sharing mechanisms, incorporate green power consumption proportions, carbon emission intensity and load adjustability into the evaluation of computing infrastructure development, and promote computing and power collaboration from policy-driven to market-driven.
